Why AI-coded apps need a security check
AI coding tools are built for speed, and speed is where security details get skipped. To make an example work, a model will often paste a real key into a file, put a secret in code that runs in the browser, or leave a database wide open. None of that is obvious while you are building, and some of it is invisible once the app is deployed. That is why a quick check before launch is worth the minute it takes.
Pre-launch security checklist
No real secrets in your source or Git history
The most common launch-day incident is a real API key committed to a public repo. Deleting it from the latest commit is not enough, because old commits stay public. If a key was ever pushed, rotate it.
Secrets live in environment variables, not code
Keys, tokens, and database URLs belong in server-side environment variables. A secret placed in client-side code is shipped to every visitor's browser and is readable by anyone.
Database access rules are on
If you use a hosted database, confirm access rules (such as row level security) are enabled and that the powerful admin key is never used in the browser.
Dependencies are not obviously outdated or risky
AI-generated projects can pin old or unusual packages. Check for known-vulnerable dependencies before you ship.
You have a way to re-check after each fix
Security is not one-and-done. Use a scan you can re-run so you can confirm a fix actually removed the issue.
Check the source, not just the live site
A check that only looks at your deployed site misses files that never render in the browser and your Git history, where old secrets live on. Reading the repository source catches a leaked key even after it is gone from the running app. ShipSafeScan does this and returns a reproducible score, so the same commit always gives the same result and you can confirm a fix.
Launching from a specific tool?
The most common mistakes differ by tool. Pick yours for a focused checklist:
Frequently asked questions
Is it safe to launch an app I built with AI?
It can be, but AI-generated code often ships with leaked secrets, keys in client code, or missing access rules. Before you launch, scan your public repository for exposed secrets and risky patterns and fix what you find.
How do I know if my AI-built app leaked an API key?
Paste your public GitHub repository URL into ShipSafeScan. It reads the source and Git history, flags hardcoded keys and secrets, masks them, and reports them with a score. If a key is flagged, rotate it and move it to an environment variable.
What is the most common security mistake in vibe-coded apps?
A real secret committed to a public repository. AI tools frequently inline a working key so an example runs, and that file gets pushed. Because Git history is public, the key stays exposed until it is rotated.
Do I need to scan if my repo is private?
A private repo lowers the exposure risk, but secrets in code are still a problem if the repo is ever made public, shared, or leaked. This version of ShipSafeScan scans public repositories.